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231
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CVPR
2010
IEEE
14 years 26 days ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu
113
Voted
CVPR
2006
IEEE
16 years 5 months ago
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
This paper presents a method for recognizing scene categories based on approximate global geometric correspondence. This technique works by partitioning the image into increasingl...
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce
117
Voted
ICPR
2002
IEEE
16 years 4 months ago
Unsupervised Learning Using Locally Linear Embedding: Experiments with Face Pose Analysis
This paper considers a recently proposed method for unsupervised learning and dimensionality reduction, locally linear embedding (LLE). LLE computes a compact representation of hi...
Abdenour Hadid, Matti Pietikäinen, Olga Kouro...
150
Voted
ICCV
2009
IEEE
15 years 1 months ago
Consensus set maximization with guaranteed global optimality for robust geometry estimation
Finding the largest consensus set is one of the key ideas used by the original RANSAC for removing outliers in robust-estimation. However, because of its random and non-determinis...
Hongdong Li
130
Voted
CVPR
2006
IEEE
16 years 5 months ago
Model Order Selection and Cue Combination for Image Segmentation
Model order selection and cue combination are both difficult open problems in the area of clustering. In this work we build upon stability-based approaches to develop a new method...
Andrew Rabinovich, Serge Belongie, Tilman Lange, J...